Conditional diagnosability of alternating group networks under the PMC model

Research output: Contribution to journalArticlepeer-review

16 Citations (Scopus)

Abstract

Fault diagnosis of processors has played an essential role when evaluating the reliability of multiprocessor systems. In many novel multiprocessor systems, their diagnosability has been extensively explored. Conditional diagnosability is a useful measure for evaluating diagnosability by adding a further condition that all neighbors of every node in the system do not fail at the same time. In this paper, we study the conditional diagnosability of n-dimensional alternating group networks ANn under the PMC model, and obtain the results tc(AN4) = 5, and tc(ANn) = 6n − 17 for n ≥ 5. In addition, for the isomorphism property between ANn and Sn,k with k = n−2, namely (n, n − 2)-star graphs Sn,n−2, the above results can be extended to Sn,n−2, and we have tc(S4,2) = 5 and tc(Sn,n−2) = 6n − 17 for n ≥ 5. It is worth noting that the conditional diagnosability is about six times the degree of ANn and Sn,n−2, which is very different from general networks with a multiple of four.

Original languageEnglish
Article number9127106
Pages (from-to)1968-1980
Number of pages13
JournalIEEE/ACM Transactions on Networking
Volume28
Issue number5
DOIs
Publication statusPublished - 2020 Oct

All Science Journal Classification (ASJC) codes

  • Software
  • Computer Science Applications
  • Computer Networks and Communications
  • Electrical and Electronic Engineering

Fingerprint

Dive into the research topics of 'Conditional diagnosability of alternating group networks under the PMC model'. Together they form a unique fingerprint.

Cite this